A literature review of UAV 3D path planning
3D path planning of unmanned aerial vehicle (UAV) targets at finding an optimal and
collision free path in a 3D cluttered environment while taking into account the geometric …
collision free path in a 3D cluttered environment while taking into account the geometric …
Anymal parkour: Learning agile navigation for quadrupedal robots
Performing agile navigation with four-legged robots is a challenging task because of the
highly dynamic motions, contacts with various parts of the robot, and the limited field of view …
highly dynamic motions, contacts with various parts of the robot, and the limited field of view …
A survey on inspecting structures using robotic systems
Advancements in robotics and autonomous systems are being deployed nowadays in many
application domains such as search and rescue, industrial automation, domestic services …
application domains such as search and rescue, industrial automation, domestic services …
Path planning method with improved artificial potential field—a reinforcement learning perspective
The artificial potential field approach is an efficient path planning method. However, to deal
with the local-stable-point problem in complex environments, it needs to modify the potential …
with the local-stable-point problem in complex environments, it needs to modify the potential …
An accurate UAV 3-D path planning method for disaster emergency response based on an improved multiobjective swarm intelligence algorithm
Planning a practical three-dimensional (3-D) flight path for unmanned aerial vehicles (UAVs)
is a key challenge for the follow-up management and decision making in disaster …
is a key challenge for the follow-up management and decision making in disaster …
Learning model predictive control for iterative tasks. a data-driven control framework
A learning model predictive controller for iterative tasks is presented. The controller is
reference-free and is able to improve its performance by learning from previous iterations. A …
reference-free and is able to improve its performance by learning from previous iterations. A …
Sampling-based algorithms for optimal motion planning
During the last decade, sampling-based path planning algorithms, such as probabilistic
roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well …
roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well …
Polynomial trajectory planning for aggressive quadrotor flight in dense indoor environments
We explore the challenges of planning trajectories for quadrotors through cluttered indoor
environments. We extend the existing work on polynomial trajectory generation by …
environments. We extend the existing work on polynomial trajectory generation by …
[KSIĄŻKA][B] Small unmanned aircraft: Theory and practice
Autonomous unmanned air vehicles (UAVs) are critical to current and future military, civil,
and commercial operations. Despite their importance, no previous textbook has accessibly …
and commercial operations. Despite their importance, no previous textbook has accessibly …
Anytime motion planning using the RRT
The Rapidly-exploring Random Tree (RRT) algorithm, based on incremental sampling,
efficiently computes motion plans. Although the RRT algorithm quickly produces candidate …
efficiently computes motion plans. Although the RRT algorithm quickly produces candidate …